Please use this identifier to cite or link to this item: https://dspace.iiti.ac.in/handle/123456789/17166
Title: On Performance of RIS-NOMA Assisted Heterogeneous ISAC Networks
Authors: Bhatia, Vimal B.
Keywords: integrated sensing and communication;Non-orthogonal multiple access;reconfigurable intelligent surfaces
Issue Date: 2025
Publisher: Institute of Electrical and Electronics Engineers Inc.
Citation: Parihar, A. S., Singh, K., Bhatia, V. B., Li, C., & Ding, Z. (2025). On Performance of RIS-NOMA Assisted Heterogeneous ISAC Networks. IEEE Transactions on Cognitive Communications and Networking. https://doi.org/10.1109/TCCN.2025.3622346
Abstract: As 6G evolves and moves towards denser heterogeneous networks, advanced technologies like non-orthogonal multiple access (NOMA), reconfigurable intelligent surfaces (RIS), and integrated sensing and communication (ISAC) are becoming increasingly important to enhance network efficiency. This paper presents a new analytical framework to assess downlink transmissions in heterogeneous networks (HetNets). The framework uses homogeneous Poisson point processes (PPP) to model the spatial distribution of base stations (BSs) and users. In the t-th tier, the BS utilizes a superimposed NOMA signal for target sensing. RISs, also modeled with homogeneous PPP, are deployed to address blockage issues when the direct link from BSs to users is unavailable. The approximated outage probability expressions are derived for two distinct scenarios: one where a typical user has a direct link to a tagged BS and one where the direct link is absent. The analysis also incorporates practical challenges such as imperfect successive interference cancellation and hardware impairments on both the transmitter and the receiver sides. The results demonstrate the benefits of RIS-NOMA over traditional orthogonal multiple access HetNets, with the performance improving as the number of RIS elements increases. Additionally, approximated expressions for ergodic rates, system throughput, and the probability of detection for sensing performance are derived. © 2025 Elsevier B.V., All rights reserved.
URI: https://dx.doi.org/10.1109/TCCN.2025.3622346
https://dspace.iiti.ac.in:8080/jspui/handle/123456789/17166
ISSN: 2332-7731
Type of Material: Journal Article
Appears in Collections:Department of Electrical Engineering

Files in This Item:
There are no files associated with this item.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

Altmetric Badge: